Arizona MTBS Thematic Burn Severity Mosaic (1996)
Metadata:
- Identification_Information:
-
- Citation:
-
- Citation_Information:
-
- Originator: Monitoring Trends in Burn Severity Program
- Publication_Date: 20170720
- Title:
-
Arizona MTBS Thematic Burn Severity Mosaic (1996)
- Geospatial_Data_Presentation_Form: raster dataset
- Online_Linkage:
-
<https://www.mtbs.gov/viewer/index.html>
- Description:
-
- Abstract:
-
The Monitoring Trends in Burn Severity (MTBS) Program assesses the frequency, extent, and magnitude (size and severity) of all large fires (includes wildfire, wildland fire use, and prescribed fire) in the conterminous United States (CONUS), Alaska, Hawaii, and Puerto Rico for the period 1984 and beyond. All fires reported as greater than 1,000 acres in the western U.S. and greater than 500 acres in the eastern U.S. are mapped across all ownerships. MTBS produces a series of geospatial and tabular data for analysis at a range of spatial, temporal, and thematic scales and are intended to meet a variety of information needs that require consistent data about fire effects through space and time. This map layer is a thematic raster image of MTBS burn severity classes for all inventoried and mappable fires occurring in Arizona during calendar year 1996.
- Purpose:
-
The primary objective of MTBS is to provide consistent burn severity data and fire perimeters for all large fires within the United States. The datasets are generated using a standardized process and produced at a resolution of 30 meters. The program provides data and products to four primary user groups including national policy-makers, field management units, other federal programs such as LANDFIRE and academic and agency research entities. These groups benefit from the availability of GIS data produced in multiple formats, as well as easy-to-read published maps.
- Time_Period_of_Content:
-
- Time_Period_Information:
-
- Single_Date/Time:
-
- Calendar_Date: 1996
- Status:
-
- Progress: Complete
- Maintenance_and_Update_Frequency:
-
Dataset contains thresholded burn severity data available for the specified mapping zone at time of publication. Dataset may be updated as burn severity data for additional MTBS fires are completed, or otherwise revised as necessary.
- Spatial_Domain:
-
- Bounding_Coordinates:
-
- West_Bounding_Coordinate: -1568955.0
- East_Bounding_Coordinate: -1181025.0
- North_Bounding_Coordinate: 1652955.0
- South_Bounding_Coordinate: 1157895.0
- Keywords:
-
- Theme:
-
- Theme_Keyword: Burned Area
- Theme_Keyword: Burn Severity
- Theme_Keyword: MTBS
- Theme_Keyword: Wildland Fire
- Theme_Keyword: Wildfire
- Theme_Keyword: Prescribed Fire
- Theme_Keyword: Landsat
- Theme_Keyword: differenced Normalized Burn Ratio
- Theme_Keyword: Normalized Burn Ratio
- Theme_Keyword: Wildfire
- Theme_Keyword: Fire Severity
- Place:
-
- Place_Keyword: United States
- Place_Keyword: Arizona
- Access_Constraints:
-
All MTBS datasets are available for download from the MTBS program website
- Use_Constraints:
-
There are no restrictions on use, except for reasonable and proper acknowledgement of information sources.
- Point_of_Contact:
-
- Contact_Information:
-
- Contact_Organization_Primary:
-
- Contact_Organization: Monitoring Trends in Burn Severity program
- Contact_Instructions: <https://www.mtbs.gov/contact>
- Data_Set_Credit:
-
Monitoring Trends in Burn Severity program (U.S. Geological Survey and USDA Forest Service)
- Security_Information:
-
- Security_Classification_System: None
- Security_Classification: Unclassified
- Security_Handling_Description: None
- Native_Data_Set_Environment:
-
Microsoft Windows 7 Enterprise Service Pack 1; ESRI ArcCatalog <IP_ADDRESS>52
- Data_Quality_Information:
-
- Attribute_Accuracy:
- Logical_Consistency_Report:
-
No tests for logical consistency have been performed on this map layer.
- Completeness_Report:
-
Data completeness reflects the availability of fire occurrence information and/or availability of suitable Landsat Thematic Mapper imagery, and the current progression of processing by the MTBS program in the specified mapping zone. In some areas, fires smaller than the specified MTBS thresholds may be present. These fires were mapped using MTBS mapping protocols to meet the data/information needs of other unrelated programs, but are included in the MTBS database.
- Lineage:
-
- Process_Step:
-
- Process_Description:
-
For a detailed definition and discussion on the processing and production of MTBS geospatial data, please refer to <http://www.mtbs.gov>. Otherwise a synopsis of the production of this layer is provided below.
MTBS burn severity class data are derived from Landsat Thematic Mapper data. A pre-fire scene and a post-fire scene are analyzed to create a Differenced Normalized Burn Ratio (dNBR) image. The continuous dNBR image portrays the variations of burn severity within the fire. In exceptional circumstances, a suitable pre-fire image may not be available to generate a dNBR . Consequently, in these circumstances, analysis and assessment is conducted using the post-fire NBR image only.
The MTBS program utilizes Landsat images produced by two USGS product generations sytems - the National Landsat Archive Production System (NLAPS) and the Level 1 Product Generation System (LPGS). NLAPS imagery are terrain corrected and geometrically rectified to an Albers Conical Equal Area map projection. The NLAPS images are further processed to convert bands 1-5 and 7 to at-satellite-reflectance. LPGS imagery are terrain corrected, geometrically rectified to Universal Transverse Mercator (UTM) projection, converted to at-satellite-reflectance, and subsequently reprojected to Albers Conical Equal Area map projection.
For each mapped fire, the Normalized Burn Ratio (NBR) is computed for each date of imagery using the following formula:
((Band 4 - Band 7) / (Band 4 + Band 7)) x 1000 = NBR
The differenced NBR is computed by subtracting the post-fire NBR from the pre-fire NBR:
PreNBR - PostNBR = dNBR
The perimeter of the fire is delineated using the dNBR and post-fire reflectance image. Continuous dNBR data are then thresholded into burn severity classes with higher dNBR values correlated to higher burn severities and lower dNBR values relating to less severe burn severites. The dNBR image for each fire is evaluated to determine the appropriate dNBR threshold to discriminate between burned and unburned areas, and low, modererate and high severity areas. For some fires, an increased response in vegetation productivity may result (areas of very low (negative) dNBR values) and are identified as areas of "Increased Greenness". Additionally, non-land surface features or areas occluded by obscurations in the pre or post-fire Landsat image are masked out (i.e. large water bodies, clouds, shadows, smoke, snow, etc.) and identified as "Non-Processing Areas".
The completed thresholded burn severity images for each each year are mosaicked to create a seamless thresholded burn severity image. The entire burn severity classification for fires that intersect the specified geographic region are maintained in the mosaic. The mosaicking process utilizes a maximum overlap function where pixels in overlapping areas of two or more input images will result in the assignment of the maximum pixel value. This situation is very rare and would potentially only happen in a slight overlap area of adjacent fires occurring in the same year.
- Spatial_Data_Organization_Information:
-
- Direct_Spatial_Reference_Method: Raster
- Raster_Object_Information:
-
- Raster_Object_Type: Pixel
- Row_Count: 16502
- Column_Count: 12931
- Vertical_Count: 1
- Spatial_Reference_Information:
-
- Horizontal_Coordinate_System_Definition:
-
- Planar:
-
- Map_Projection:
-
- Map_Projection_Name: Albers_Conical_Equal_Area
- Albers_Conical_Equal_Area:
-
- Standard_Parallel: 29.5
- Standard_Parallel: 45.5
- Longitude_of_Central_Meridian: -96.0
- Latitude_of_Projection_Origin: 23.0
- False_Easting: 0.0
- False_Northing: 0.0
- Planar_Coordinate_Information:
-
- Planar_Coordinate_Encoding_Method: row and column
- Coordinate_Representation:
-
- Abscissa_Resolution: 30.0
- Ordinate_Resolution: 30.0
- Planar_Distance_Units: meters
- Geodetic_Model:
-
- Horizontal_Datum_Name: North American Datum of 1983
- Ellipsoid_Name: Geodetic Reference System 80
- Semi-major_Axis: 6378137.000000
- Denominator_of_Flattening_Ratio: 298.257222
- Entity_and_Attribute_Information:
-
- Detailed_Description:
-
- Entity_Type:
-
- Entity_Type_Label: mtbs_AZ_1996.tif
- Attribute:
-
- Attribute_Label: ObjectID
- Attribute_Definition: Internal feature number.
- Attribute_Definition_Source: ESRI
- Attribute_Domain_Values:
-
- Unrepresentable_Domain:
-
Sequential unique whole numbers that are automatically generated.
 Thresholds are based on interpretation by MTBS analysts in the context of available ancillary data. Determination of thresholds are also based on established relationships between composite burn index (CBI) ground plot data and dNBR values where available.
- Entity_and_Attribute_Detail_Citation: MTBS Thresholded Burn Severity
- Distribution_Information:
-
- Distributor:
-
- Contact_Information:
-
- Contact_Organization_Primary:
-
- Contact_Organization: Monitoring Trends in Burn Severity (MTBS) program
- Contact_Instructions: <https://www.mtbs.gov/contact>
- Resource_Description: Downloadable Data
- Distribution_Liability:
-
This product is produced from MTBS geospatial information prepared by the U.S. Department of Agriculture, Forest Service and U.S. Geological Survey EROS. By taking receipt of these files via electronic file transfer methods, you understand that the data may be updated due to the availability of additional data or revision of existing data. Represented features may not be in an accurate geographic location. The Forest Service and USGS EROS make no expressed or implied warranty, including warranty of merchantability and fitness, with respect to the character, function, or capabilities of the data or their appropriateness for any user's purposes. The Forest Service and USGS EROS reserve the right to correct, update, modify, or replace this geospatial information without notification.
- Standard_Order_Process:
-
- Digital_Form:
-
- Digital_Transfer_Information:
-
- Format_Name: GeoTiff
- Transfer_Size: 3.8 MB
- Metadata_Reference_Information:
-
- Metadata_Date: 20170720
- Metadata_Contact:
-
- Contact_Information:
-
- Contact_Organization_Primary:
-
- Contact_Organization: Monitoring Trends in Burn Severity
-
- Contact_Instructions: <https://www.mtbs.gov/contact>
- Metadata_Standard_Name: FGDC Content Standards for Digital Geospatial Metadata
- Metadata_Standard_Version: FGDC-STD-001-1998
- Metadata_Time_Convention: local time
- Metadata_Extensions:
- Metadata_Extensions:
-
- Online_Linkage: <http://www.esri.com/metadata/esriprof80.html>
- Profile_Name: ESRI Metadata Profile


| What? | When? | Location |
|---|---|---|
| Paris Web 2007 | 2007-11-15 | IBM La Defense / INSIA |
| Paris On Rails 2007 | 2007-12-10 | Cite des Sciences |
| Burger Quiz party | 2007-04-14 | Volta |
| First name | Last name | Latest checkin |
|---|---|---|
| Richard | Piacentini | 2007-03-27 |
| Eric | Daspet | 2007-03-28 |
| Aurore | Jaballah | 2007-03-15 |


Carol G. Pace
Democrat
Retired health/higher ed. administrator
BA Economics, University of California Santa Cruz MS Administration, University of California Irvine FACMPE - Lifetime Fellow in the American College of Medical Practice Executives Volunteer Income Tax Assistance/VITA/TCE Advanced Certification
80231
I have been continuously registered to vote and vote in all elections in accordance with my Colorado residency. I attend neighborhood meetings, townhalls, and local party meetings and have actively participated in caucuses, signing of political petitions and low-key fundraising events. I have occasionally performed unpaid voluntary work in behalf of political candidates. In behalf of League of Women Voters of Colorado (LWVCO), a non-partisan volunteer organization, I have assisted with non-partisan voter registration drives and have otherwise promoted voting. In behalf of LWVCO I have delivered non-partisan ballot measure talks to inform voters of ballot measures, these talks to groups such as seniors in assisted living facilities, neighborhood associations, and small businesses. I have not been paid for any political activities nor elected to any positions within a political party. Campaign contributions Hillary Clinton/Democratic Party 2016 Biden Campaign/Democratic Party-2020 Minor contributions/silent auction/merchandise purchase – less than $100 for any candidate or campaign
Political-all volunteer Democratic Party of Colorado/Denver Civic – all volunteer roles League of Women Voters of Colorado, Board, Director At-Large, 2008-present League of Women Voters of Denver – City Government Committee, Environment Committee, Healthcare Committee, Speakers Bureau, Program Council, Board Member, 2008-present AARP Colorado Statewide Advocacy Committee, Volunteer Advocate, 2012-present AARP Tax-Aide Program, Volunteer Counselor, Denver, Aurora, 2013-2017 Colorado Consumer Health Initiative (CCHI) Policy Committee, Member, Co-Chair, 2011-present Boomers Leading Change In Healthcare (BLCIH)/Boomers Leading Change (BLC), 2011-present Denver Water, Citizens Advisory Committee (CAC), Denver Representative, 2012-2015 Public Service Credit Union Supervisory Committee, 2008-2011 Connect for Health Colorado (formerly COHBE), Health Plan Advisory Group & other planning roles Building a Better Colorado, volunteer participant, 2015-present Volunteer Organizations National History Day in Colorado (NHDC), Colorado middle schools/high schools, Judge, Denver, Metro, Regional, State levels 2007-present Colorado High School Activities Assn (CHSAA) Debate Judge 2012-2015 Toastmasters International (TI), Member, Area Director, Division Director, 1987-present Volunteers for Outdoor Colorado Sierra Club Professional Organizations Lifetime Fellow, American College of Medical Practice Executives, Medical Group Management Assn. Lifetime Member, Medical Group Management Assn. Appointments – Boards & Commissions (all voluntary) State Innovation Model (SIM), Consumer Representative 2015-2019 Consumer Insurance Council (CIC), Division of Insurance, Member, Secretary, 2016-2018 Consumer Insurance Council (CIC), Division of Insurance, Member, Chair, 2020-present Strategic Action Planning Group on Aging (SAPGA), Health Committee, 2016
Two statewide associations that I provide volunteer consumer advocacy for include AARP Colorado and League of Women Voters of Colorado. As a volunteer advocate for AARP Colorado I participate in senior advocacy (age 50 and older), specifically representing that group as a stakeholder during Colorado legislative session. I follow bills, research, prepare positions & make recommendations, which may involve my providing oral or written testimony at the legislature. My concentration is on bills related to health care systems & affordability, Medicaid, Medicare, public pensions, as well as other issues such as affordable housing, utilities, financial security for seniors and the state budget. Similarly as a volunteer advocate for League of Women Voters of Colorado I participate in advocacy at the legislature for bills they support, including providing oral testimony, and representing League as a stakeholder in legislative issues. Their issues include healthcare, mental health, juvenile justice, environmental issues, voter services as well as developing the redistricting legislation which led to the upcoming Redistricting Commission. I’ve been on multiple Speakers Bureaus, including for Bureau of the Census, AARP, LWVCO, LWVD. I’ve assisted groups in Southwest Colorado, in Durango and Grand Junction with access to remote testimony to the legislature. I’ve provided volunteer AARP Tax Aide services in the Denver/Aurora area to low income as well as to seniors. As a property owner and with family in multiple jurisdictions of the state I have been involved in housing, land-use, real estate and other functions in Denver, Boulder and Durango.
The redistricting commission has the unique capacity to advance increasingly neutral and fair maps for a state based on geographic, demographic criteria and other criteria important to the state. The opportunity to participate in that outstanding opportunity is what appeals to me.
Working in voluntary non-partisan organizations like AARP Colorado and League of Women Voters Colorado has given me the opportunity to hear varied viewpoints and promote consensus at the grassroots level. In a commission role I would contribute experience in gathering input, using technology and research tools, and embracing the input around the state to conduct the work of the commission and produce the optimum maps for fairness and impartiality.
With an undergraduate degree in Economics, a master’s degree in Administration, and a career in administration, finance, business, and operations, I am familiar with being presented with a variety of theoretical as well as real-live experiences with problem-solving which involved people (staff, clients, patients), space, budgets and varying viewpoints. As a volunteer consumer advocate in my retirement, I am interested in addressing multiple viewpoints, reaching consensus and working toward win-wins. I am comfortable with technical software and have experience with: Researching online Brainstorming Writing Communications-public speaking MS Office Spreadsheets Presentation software Tax software, which I used as a volunteer AARP Tax-Aide Counselor for many years Educational software, e.g. Cornerstone on Demand Social Media Zoom Hosting, Presenting and other online tools
Female


Techniques Using SOPs
Particle Life as Scale
The particle SOP has a number of interesting uses, and one of them is for driving instancing-based systems. Here we get another example of instances based on the position of our particles. This is often helpful as particles have a number of forces they react to. Before physics was included in TouchDesigner, particles could be set to die or bounce based on collision with other SOPs.
Perhaps more interesting for us in this example is that particles carry an attribute for life. When we convert our SOP to a CHOP we see two life attributes — “l1” describes the particles current life (how long it’s been present), and “l2” describes the total life of the particle (how long it will live). These raw values are useful, but perhaps more important for us here is to convert these two numbers into a single normalized value. A normalized value is easier to scale, and can be used in conjunction with other CHOPs like the look-up CHOP. Here a select CHOP and math CHOP are used to isolate the desired channels, and then derive the normalized life for the particle (current life / life-span). The range parameters of the math CHOP are also used so the spheres shrink over the course of their life, rather than growing.
Tested in TouchDesigner099 2020.23680
Updated 06.03.20
Matthew Ragan
Zoe Sandoval


Radom Quote Generator
Some inspirirational quotes to get you through the day.
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Hello World
-The World


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Testing in a virtual environment first can help determine the right set of packages.
With sudo -i -u postgres, create a new database called “helios”
Move to the git repo and install the required dependencies with pip3 install -r requirements.txt
Run py3 manage.py makemigrations, py3 manage.py migrate to configure the database.
Start rabbitmq with servicectl rabbitmq-server start
Start celery with celery -A helios worker -l info
In a new window, go to settings.py and edit the allowed hosts to [‘*’] (this means all), set the URL to localhost or the production url, set the timezone, secret key, … and add google/facebook/social media credentials.
Go to the google developer console and create a new web app with authorized JS origin = http://<IP_ADDRESS>:8000 as well as your site name, if you have one. Set redirect URL as http://localhost:8000/auth/after/ and also similar with your site name if available. Enable the Google+ and Google People APIs
Add nonsensitive scopes:
Run py3 manage.py runserver with optional arg <IP_ADDRESS>:8000 to run for production.
No web server is necessary if you use “screen” to run celery and Helios in the background. “bg” will not work long-term.
Apache and nginx are both compatible with Helios. We used nginx and gunicorn for one of our website versions
As of early 2021, the installation instructions for Helios are missing the celery command above. The steps above are what we use to set up our helios testing servers.


This data shows the percentage of adults (ages 18 and older) who thought about commiting suicide in the past year. The respondents were given a questionare.  Those who answered yes are shown in this data set. The data was collected between 2012 -2014.
This data shows the percentage of adults (ages 18 and older), who had a major depressive episode. In this data major depressive episode was classified based on the criterias of the Diagnostic and Statistical Manual of Mental Disorders—Fourth Edition(DSM-IV). The data was collected between 2012 -2014. The confidence interval is also shown, this is a percentage that says something about how confident we can be that the observed value is correct over the population of each state.


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Represents the display. Scene is a special Figure class that is the root of all active Figures. Adding a child Figure to the Scene causes a new window to be displayed. Normally, only one Scene object is defined in an application's Process::main() routine. Main then adds child figures for each root window of the application (again, normally just one) and then calls Scene::nextAction() to get and process action commands from the user interface. This command processing loop terminates with a particular command (eg: "quit") and Process::main then exits.
In addition, the Scene class has a number of query methods to determine characteristics of the display and to control overall display / keyboard / mouse activity.
| Scene() | Constructor. |
| addFrame() | Add a frame figure to the scene. |
| getScreen() | Return the name of the screen where this scene is displayed. |
| nextAction() | Start / Continue user interface processing. |
| removeFrame() | Removes a Figure from the Scene. |
| setFlashRate() | Sets the flash rate in milliseconds. |
| ~Scene() | Destructor. |
Scene(String strScreen="", int msecFlashRate=0)
Constructor. The first optional parameter is a platform dependent string indicating which display head to connect to.
On UNIX, it's syntax is the same as the X DISPLAY environment variable or a -display parameter.
If the string is null, then the created Scene represents the default display in the users environment.
The second optional parameter is the flash rate in milliseconds. Zero indicates no flash, One indicates that the rate should be synchronized with the vertical retrace.
void Scene::addFrame( Figure* pfig )
void Scene::addFrame( Figure* pfig, LogPos lposWidth, LogPos lposHeight )
void Scene::addFrame( Figure* pfig, LogPos lposX, LogPos lposY, LogPos lposWidth, LogPos lposHeight )
Add a frame figure to the scene. Positions and sizes can be specified, but these may or may not be honored by the windowing system.
By default, the child is asked for it's desired size and location. If the size returned is FullWindow, then a platform dependent size is chosen (1/4 of the screen or more).
const String& Scene::getScreen()
Return the name of the screen where this scene is displayed. This may be different from the Screen string passed to the constructor.
const String& Scene::nextAction()
Start / Continue user interface processing. This method starts an event processing loop that results in method calls on active figures.
The loop continues until a "doAction" call is made that propogates to the screen. The action command is queued and then returned by this routine after event processing finishes.
It is an error to call this routine if no Figures are active.
void Scene::removeFrame( Figure* pfig )
Removes a Figure from the Scene.
void Scene::setFlashRate( int msec )
Sets the flash rate in milliseconds. Zero indicates no flash, One indicates that the rate should be synchronized with the vertical retrace.
Scene::~Scene() throw()
Destructor. Removes all child Figures from the Display and terminates the graphical user interface of the application.


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The Misadventures of an Aussie Blogger. . I have just added a suicide prevention page to the blog. It contains a link that will help . He's twinkalicious Blog this!
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Sep 22, 2008. Fable men continues, this installment features the twinkalicious Boy Blue. . Scans courtesy of Jimmy, you can visit his blogs here and here.
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twinkalicious at blog spot Herniated or Bulging Discs
VincentLambert.com: New Release: Twinkalicious 2
Aug 18, 2008 . 8teenboy pulls out all the stops in this fun five-scene sequel to 2005's Twinkalicious. The action is intense and the guys' libidos are on fire as .
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Raw Masculinity
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Too Much Information: June 2006
Jun 29, 2006. Life of Ethan Green opens this week, starring the oh-so twinkalicious Daniel Letterle. . Wonder why I have all of those words on my blog.
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Oct 31, 2008 . These boys are so twinkalicious that by comparison Zac Efron seems like Charles Bronson. Posted by Vera at . Blogs of Note (May be NSFW.) .
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Baxter's Briefs: Review - Twinkalicious 3
May 27, 2010 . It doesn't take much arm twisting to distract Skyelr Bleu from his Youtube watching as the adorable blonde Cody Cachet puts the move on him .
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Adventures in Group Sex
13 hours ago . This blog lists the M4M group sex parties in New York. All the parties offer different dynamics, some just hot guys, some mixed, some intense, .
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Medical-Vocational Allowance for Herniated Disc
Baxter's Briefs: Twinkalicious 3 (Stills)
May 28, 2010 . My Photo. Baxter's Briefs: It's hard (insert pun here) to believe I began reviewing porn back in 2000, on a whim, and have since reviewed over .
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Kris Klein's XXX Files: Hunky Interview: KAYDEN DANIELS
Dec 2, 2009 . Recently, among other twinkfests, I was sent a screener for a film from 8teenboy with the unique title Twinkalicious 2. . Teazed.blogspot.com .
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Appealing a Denial of Benefits
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Oct 2, 2012 . http://delvallearchives.blogspot.com/ . and Johnathan Rhys-Meyers is at his twinkalicious best in a fearless performance as Brian Slade, the .
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Artful Women exhibit empowers women, gives them a voice
by Emilie BurdittMADISON, Wis. - In an effort to empower women, artists raised funds through the Artful Women exhibit. Their artwork is displayed at University of Wisconsin Health.
A reception Sunday honored the 46 artists, and based off a judge's opinion, some artists were given prizes. The art was judged on innovation, aesthetics and ideas.
Mandy Kron, UW Health art coordinator, said the artwork gives women a voice. Money raised from the purchased art is given back to the artists and to the Wisconsin Women's Network, which is a nonprofit organization that works throughout Wisconsin to advance the lives of women and girls.
"I think (the art exhibit) gets their message out to a lot of people," Kron said. "We have so many people coming through the hospital here that get to see that and hopefully know about the programs they do."
People can buy the art at UW Health, where it'll be displayed until Dec. 6.


Viral image shows scale of melting ice in Greenland
A photo showing sled dogs wading through water ankle-deep on top of a melting ice sheet in Greenland has gone viral. The picture taken by Steffen Olsen from the Centre for Ocean and Ice at the Danish Meteorological Institute shows the scaling of melting ice in Greenland. Olsen said the ice sheet beneath the water for 1.2 metres thick.
short by Ankush Verma


I'm Pre-Final year Undergraduate Studying at Ramgarh Engineering College, Ramgarh,Jharkhand. Exploring new technologies out there and updating my skillset.I have great interest in knowing new things about computer so I opted science stream after 10th. I had aimed to study computer science from my school times and my dream came true. In my school times also use to participate in science fair and many more competitive exam like Science,Maths,English Olympiads. Talking about my Skills, I have a good knowledge on c/c++(programing language),html,css, bootstrap,node.js,wordpress. I also do a lot of Competitive Programming which I have started few months back and I'm still improving in same as well. I'm currently working on Project to inhance my skills. My future goal aims to do a internship in big tech IT firm for gaining real world experience.


Dashboard
Qualifications
Dr. License
Birthdate
Total Records
Recent Patients
| Record Id. | Patient Id. | Type | Problem | Institute Id. | View |
|---|


Q1. When you think of the times in your life where you’ve been the happiest, the proudest, or the most satisfied, which of the following values come to mind?
A. Accomplishment, Activism, Adventure, Affection, Challenge, Confidence, Cooperation Creativity, Excitement, Friendships, Health, Helping other people, Honesty, Integrity, Leadership, Romance
Q2. Pick one value and write a couple of sentences about why one of the values you chose is important to you.
A. Adventure is an important value to me because it encompasses a lot of the others mentioned above. My favorite thing to do is go on adventures with my wife. This could be anything from traveling to a new place or jumping into a new life event. We both seem to get a charge out of new things no matter how big or small. Adventure can also often mean change. I tend to embrace change and not let the fear of something new or different get the best of me.
Q3. Answer the following for the values you chose in Exercise 1: In general, I try to live up to these values: Disagree 1 ----- 2 ----- 3 ----- 4 ----- 5 Agree
A. I would choose 5 for all of the values above. I feel like I will always be working toward these goals.
Q4. What was the last topic that someone asked for your advice on?
A. A colleague asked me how to go about addressing a difficult work situation. I felt honored that they came to me with this concern.


| # | From - To | Date | Package | Additional Services | Price | Actions |
|---|---|---|---|---|---|---|
| {{ id }} | Earth - Mars | 2020/10/1{{ id }} - 2020/10/2{{ id }} | Hotel Catering Guide | 566,99 |
| # | From - To | Date | Package | Additional Services | Price |
|---|---|---|---|---|---|
| {{ id }} | Earth - Mars | 2020/10/10 - 2020/10/15 | Hotel Catering Guide | 566,99 |
| # | From - To | Date | Price | Cancellation reason |
|---|---|---|---|---|
| {{ id }} | Earth - Mars | 2020/10/10 - 2020/10/15 | 566,99 | Wrong order |


data HIV Health routine testing systems surveillance information care {border-style quality px;} #ffffff;} Data clinical inform prevention provide treatment health new populations potential Public national patient sampling used World []. need strategic sub-Saharan collab: data, program use women improve infection monitor programs px; {font-family based collected comprehensive ensure estimates font-size incidence key methods monitoring needs persons prevalence using Africa antenatal antiretroviral assessments better collection double; individuals level local pregnant progress promote required risk service services strengthen surveys time Africa, approach assess border-color border-width coverage critical designed development existing follow-up living pathway phase platforms present prevention, promoting reducing respondent-driven results sentinel shift solid; strengthening support targeted understanding {font-style {font-weight (eg, AIDS OrganizationConsolidated School Surveillance Testing [,]. [-]. accurate action and, and/or anonymous assurance bold care, cascade: cohort collect community-based conducting courier; create developing diagnosed diagnosis efforts efforts. em; epidemic focus geographic global greater guidelines high identifying infections informing interpretation multiple number presented priorities pt;} public purposes quality, records required. scale sex studies timely track undiagnosed unlinked


| Rank | Name | Age | Description |
|---|---|---|---|
| 2 | A | 20.1 | something W |
| 3 | W | 1.9 | something Z |
| 4 | C | 80.1 | something A |
| 5 | C | N/A | something A |
| 1 | Z | 100.01 | something C |
| Rank | Name | Age | Description |
|---|---|---|---|
| 2 | A | 20.1 | something W |
| 3 | W | 1.9 | something Z |
| 4 | C | 80.1 | something A |
| 5 | C | N/A | something A |
| 1 | Z | 100.01 | something C |
| Rank | Name | Description |
|---|---|---|
| 2 | A | something W |
| 3 | A | something Z |
| 4 | A | something A |
| 5 | B | something A |
| 1 | Z | something C |
| Nelson Mandela | Steve Nash | Sasha Pieterse | J.R.R. Tolkien |
|---|---|---|---|
| 1 | 2 | 3 | 4 |
| 95 | 39 | 17 | 81 |
| Former political prisoner who upon his release was elected president of South Africa in 1994. | NBA legend who won the MVP in 2005 and 2006 with the Phoenix Suns, and played in eight NBA All-Star games. | Teen actress who played Alison DiLaurentis on the hit ABC Family series Pretty Little Liars. | English author, poet, and professor who created The Hobbit and The Lord of the Rings trilogy. |
| Nelson Mandela | Steve Nash | Sasha Pieterse | J.R.R. Tolkien |
|---|---|---|---|
| 1 | 2 | 3 | 4 |
| 95 | 39 | 17 | 81 |
| Former political prisoner who upon his release was elected president of South Africa in 1994. | NBA legend who won the MVP in 2005 and 2006 with the Phoenix Suns, and played in eight NBA All-Star games. | Teen actress who played Alison DiLaurentis on the hit ABC Family series Pretty Little Liars. | English author, poet, and professor who created The Hobbit and The Lord of the Rings trilogy. |
| Nelson Mandela | Steve Nash | Sasha Pieterse | J.R.R. Tolkien |
|---|---|---|---|
| 1 | 2 | 3 | 4 |
| 95 | 39 | 17 | 81 |
| Former political prisoner who upon his release was elected president of South Africa in 1994. | NBA legend who won the MVP in 2005 and 2006 with the Phoenix Suns, and played in eight NBA All-Star games. | Teen actress who played Alison DiLaurentis on the hit ABC Family series Pretty Little Liars. | English author, poet, and professor who created The Hobbit and The Lord of the Rings trilogy. |
| Nelson Mandela | Steve Nash | Sasha Pieterse | J.R.R. Tolkien |
|---|---|---|---|
| 1 | 2 | 3 | 4 |
| 95 | 39 | 17 | 81 |
| Former political prisoner who upon his release was elected president of South Africa in 1994. | NBA legend who won the MVP in 2005 and 2006 with the Phoenix Suns, and played in eight NBA All-Star games. | Teen actress who played Alison DiLaurentis on the hit ABC Family series Pretty Little Liars. | English author, poet, and professor who created The Hobbit and The Lord of the Rings trilogy. |
| Nelson Mandela | Steve Nash | Sasha Pieterse | J.R.R. Tolkien |
|---|---|---|---|
| 1 | 2 | 3 | 4 |
| 95 | 39 | 17 | 81 |
| Former political prisoner who upon his release was elected president of South Africa in 1994. | NBA legend who won the MVP in 2005 and 2006 with the Phoenix Suns, and played in eight NBA All-Star games. | Teen actress who played Alison DiLaurentis on the hit ABC Family series Pretty Little Liars. | English author, poet, and professor who created The Hobbit and The Lord of the Rings trilogy. |
| Nelson Mandela | 1 | 95 | Former political prisoner who upon his release was elected president of South Africa in 1994. |
|---|---|---|---|
| Steve Nash | 2 | 39 | NBA legend who won the MVP in 2005 and 2006 with the Phoenix Suns, and played in eight NBA All-Star games. |
| Nelson Mandela | 1 | 95 | Former political prisoner who upon his release was elected president of South Africa in 1994. |
|---|---|---|---|
| Steve Nash | 2 | 39 | NBA legend who won the MVP in 2005 and 2006 with the Phoenix Suns, and played in eight NBA All-Star games. |
| Nelson Mandela | Steve Nash | Sasha Pieterse | J.R.R. Tolkien |
|---|---|---|---|
| 1 | 2 | 3 | 4 |
| 95 | 39 | 17 | 81 |
| Former political prisoner who upon his release was elected president of South Africa in 1994. | NBA legend who won the MVP in 2005 and 2006 with the Phoenix Suns, and played in eight NBA All-Star games. | Teen actress who played Alison DiLaurentis on the hit ABC Family series Pretty Little Liars. | English author, poet, and professor who created The Hobbit and The Lord of the Rings trilogy. |


The Meaning of Namaste
Does your yoga teacher conclude every practice by saying “Namaste”? Learn what the Sanskrit word really means here.
The gesture Namaste represents the belief that there is a Divine spark within each of us that is located in the heart chakra. The gesture is an acknowledgment of the soul in one by the soul in another.
Definition of Namaste
Nama means bow, as means I, and te means you. Therefore, namaste literally means “bow me you” or “I bow to you.”
How to Make the Namaste Gesture
To perform Namaste, we place the hands together at the heart chakra, close the eyes, and bow the head. It can also be done by placing the hands together in front of the third eye, bowing the head, and then bringing the hands down to the heart..
This is an especially deep form of respect. Although in the West the word “Namaste” is usually spoken in conjunction with the gesture. In India, it is understood that the gesture itself signifies Namaste, and therefore, it is unnecessary to say the word while bowing.
We bring the hands together at the heart chakra to increase the flow of Divine love. Bowing the head and closing the eyes helps the mind surrender to the Divine in the heart. One can do Namaste to oneself as a meditation technique to go deeper inside the heart chakra; when done with someone else, it is also a beautiful, albeit quick, meditation.


What was intended as a set of personal practices has
become a doctrine. And despite the mainstream adoption of Agile, the
loss of its original intent has undermined its effectiveness.
March 18, 2014
URL:http://www.drdobbs.com/architecture-and-design/the-corruption-of-agile/240166698
Many people over the years have discussed their distress with the religious tone that cloaks the implementation of Agile practices. Particularly from the testing side of the world, there is a lot of "should," "should not," and "can do better next time" dialogue that sounds more like a man trying to fix ethical lapses than a developer writing code. When I speak with adherents of test-driven development (TDD) in particular, there is a seeming non-comprehension that truly excellent, reliable code was ever developed prior to the advent of this one practice. I sense their view that the long history of code that put man on the moon, ran phone switches, airline reservation systems, and electric grids was all the result of luck or unique talents, rather than the a function of careful discipline and development rigor.
The disconnect between today's Agile view and earlier reality is equally evident in the wanton bashing of the waterfall model. To get any programmer today to adopt your recommendation, simply state that not doing so is just a new way of doing waterfall. Watch his toes curl despite never having used waterfall, nor seemingly having any awareness that it served the industry really well for decades. What, was everyone in that bygone era a fool?
Alan Kay was entirely right when he said that programming today has become a pop culture: "Pop culture is all about identity and feeling like you're participating. It has nothing to do with cooperation, the past or the future it's living in the present. I think the same is true of most people who write code for money. They have no idea where [their culture came from] and the Internet was done so well that most people think of it as a natural resource like the Pacific Ocean, rather than something that was man-made. When was the last time a technology with a scale like that was so error-free?"
It will pain some readers to know that the vast, error-free Internet predates Agile and even predates TDD. Crazy, right?
What I'm saying here is certainly not new. The fascination with today's way of doing things and the view that it is the one true path to good code is a seemingly permanent part of the programming culture. But it has been greatly abetted by the legions of Agile consultants. By stressing the practices, they have corrupted what Agile was about. It's important to remember that the Agile manifesto stated values, not practices. Immediately, though, values were translated into programming practices by consultants and, quickly, the former was lost. One of the original formulators of the manifesto, Dave Thomas, whom I interviewed this week, states his realization that a month after the manifesto was written it was already being corrupted: " it got immediately productized in many different ways. The whole point, to my mind, of the Agile Manifesto is that it's a set of personal practices that may scale to team level. You do not need a consultant to show you how to do that. It may help to have someone facilitate, but you do not need a consultant. And yet immediately what happened was that everyone and their dog hung out an Agile shingle and the whole thing turned into a branding exercise."
What's interesting in Thomas's account is the view that Agile was a personal practice. Implicit is a personal way of orienting oneself towards a development process that accepts, even welcomes, change.
By pure coincidence, Allen Holub has been driving this point home in several blog posts, the most recent of which is a brilliant little piece that reminds us that Agile is a culture, not a set of practices. As he has previously explained, just because an organization is using scrum, doesn't mean it's Agile. He could have said the same thing about TDD, continuous integration, pair programming, or the like.
Whether a site is Agile or not depends on its culture. Does the culture support the personal values of the manifesto? If so, it's Agile, if not, then it's doing something else. So, indeed you could have a fully Agile site without TDD, continuous integration, or scrum. Likewise, you can have a site that uses all three practices, but cannot adapt to changes and is wholly inflexible in its work so, not at all Agile. Yeah, I know, crazy, right?
Andrew Binstock
Editor in Chief
<EMAIL_ADDRESS>Twitter: platypusguy
Terms of Service | Privacy Statement | Copyright © 2012 UBM Tech, All rights reserved.


Find
The Find Window allows the creation of sophisticated rules to be searched for, and 'matched' on a graph. An example of a Find Window can be seen below.
Major Elements of the Find Window
There are several major components found on a Find Window. They are:
- Combo-box where a selection between searching on 'Nodes' or 'Transactions' may be made. Searches will only be performed on the selected graph element type.
- Combo-box where a selection between whether 'all' (binary AND) or 'any' (binary OR) rules must be matched for a graph element to be returned as a result of a search.
- A find 'rule'. For any given search operation, one or more find rules must be created.
- An input box where the value to be matched is placed.
- A check-box that determines whether any results of a search are added to the current selection on the graph, or replace it. (Ticked indicates that the results are added.)
- Removes the find rule it appears on.
- Adds a blank find rule to the end of the list.
- Indicates the number of results found for the search.
- Button that reset the window to a single blank rule.
- Combo-box that allows the selection of the graph attribute to search on.
- Combo-box that indicates the form the search will take. For example 'contains', 'is', 'occurred on', 'is between', etc.
- Button that allows the adding of a delimited list of strings to be added.
- Option for string attributes that allows a list of values to be searched for. A comma separated list in the value input box will be searched and results returned for any matches. (List searches are performed as binary OR operations).
- Option to force case-sensitive searches on strings.
- Button that performs a search with the rules specified.
Supported Find Rule Types
There are currently 8 supported attribute types that can be searched for in various ways. Attribute types that are not registered as one of the following types will be searched as 'strings.' The types are as follows:
- Boolean searches:
- Colour searches:
- Date searches:
- DateTime searches:
- Float searches:
- Icon searches:
- String searches:
- Time searches:


A FIN TECH SOLUTION to set budgets and monitor spending for users
We all have trouble managing our money as students. Most of the time we don't even realize we go over our budget during the month. This app solves the problem by allowing the user to set goals, and connect their banking information to monitor their spending.
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Applied Unsupervised Learning Models


Before he can complete his journey to save the world, Aang needs to master the elements of water, earth, and fire in order to discover what he values most.
|
brevity—Brexit Cardin—carding cubits—Cuchulain ? redrew—reduce |
||
|
acknowledgments—acne codes—codfish leftmost—leftover Manichean—manicure metaphors—metastases ? palimpsests—paling setbacks—Seth |
||
|
alacrity—Alamo beautifying—Beauvoir herbs—herd mukluks—mulberries poaching—pock Tartuffe—taser ? |
||
|
callisthenics—callous ? gantry—Gap inwards—iodine |
||
|
? charity—charlatan Venus—Venuses |
||
|
aphoristic—Apia Apollinaire—apologetic Arequipa—Argentina artefacts—arterial atheists—atherosclerosis demesnes—demigod Dionne—Diophantine Hepburn—hepper her—herald Herman—Herminia ? zeta—Zhengzhou |
||
|
skate—skated snowblowers—snowbound ? |
||
|
anodynes—anomalies ? confining—confiscate eucalyptuses—Euclid Holt—homage matriculation—matrix penalty—pence |
Hi diary! It’s been a while, I guess. Now, what order did these all happen in?


OXB Module¶
About¶
Command Guide¶
Module OXB manages the symbol table for the Oberon compiler and reads and writes ‘smb’ files
API Guide¶
Dependencies¶
Files OXS
Constants¶
versionkey* = 1; maxTypTab = 64;
(* class values*) Head* = 0;
Const* = 1; Var* = 2; Par* = 3; Fld* = 4; Typ* = 5;
SProc* = 6; SFunc* = 7; Mod* = 8;
(* form values*) (* BYTE <= SHORTINT <= INTEGER <= LONGINT , FLOAT <= DOUBLE *)
Byte* = 1; Bool* = 2; Char* = 3; Short* = 4; Int* = 5; Long* = 6; Real* = 7; Double* = 8; Set* = 9;
Pointer* = 10; Interface* = 11; Continuation* = 12; NilTyp* = 13; NoTyp* = 14; Proc* = 15;
String* = 16; Array* = 17; Record* = 18; TProc* = 19;
Ptrs* = {Pointer, Interface, NilTyp}; Procs* = {Proc, NoTyp};
Types¶
Object* = POINTER TO ObjDesc;
Module* = POINTER TO ModDesc;
Type* = POINTER TO TypeDesc;
ObjDesc*= RECORD
class*, exno*: BYTE;
expo*, rdo*: BOOLEAN; (*exported / read-only*)
lev*: INTEGER;
next*, dsc*: Object;
type*: Type;
name*: OXS.Ident;
val* (*,val2* *): LONGINT
END ;
ModDesc* = RECORD (ObjDesc) orgname*: OXS.Ident END ;
TypeDesc* = RECORD
form*, ref*, mno*: INTEGER; (*ref is only used for import/export*)
nofpar*: INTEGER; (*for procedures, extension level for records*)
len*: LONGINT; (*for arrays, len < 0 => open array; for records: adr of descriptor*)
dsc*, typobj*: Object;
base*: Type; (*for arrays, records, pointers*)
size*: LONGINT; (*in bytes; always multiple of 4, except for Byte, Bool and Char*)
END ;
(* Object classes and the meaning of "val":
class val
----------
Var address
Par address
Const value
Fld offset
Typ type descriptor (TD) address
SProc inline code number
SFunc inline code number
Mod key
Type forms and the meaning of "dsc" and "base":
form dsc base
------------------------
Pointer - type of dereferenced object
Proc params result type
Array - type of elements
Record fields extension *)
Variables¶
topScope*, universe, system*: Object;
byteType*, boolType*, charType*: Type;
shortType*, longType*, doubleType*: Type;
intType*, realType*, setType*, nilType*, noType*, strType*: Type;
nofmod, Ref: INTEGER;
typtab: ARRAY maxTypTab OF Type;
Functions and Procedures¶
- ::
PROCEDURE NewObj*(VAR obj: Object; id: OXS.Ident; class: INTEGER); (insert new Object with name id)
- ::
PROCEDURE thisObj*(): Object;
- ::
PROCEDURE thisimport*(mod: Object): Object;
- ::
PROCEDURE thisfield*(rec: Type): Object;
- ::
PROCEDURE OpenScope*;
- ::
PROCEDURE CloseScope*;
— MakeFileName ??
PROCEDURE MakeFileName*(VAR FName: OXS.Ident; name, ext: ARRAY OF CHAR);
— ThisModule ??
PROCEDURE ThisModule(name, orgname: OXS.Ident; decl: BOOLEAN; key: LONGINT): Object;
— Read reads an adjusted byte in from the symbol file.
PROCEDURE Read(VAR R: Files.Rider; VAR x: INTEGER);
— InType reads a type in from the symbol file of an imported module.
PROCEDURE InType(VAR R: Files.Rider; thismod: Object; VAR T: Type);
— Import reads in the symbol file for an imported module so that its exported constants, types, variables, and procedures may be referenced.
PROCEDURE Import*(VAR modid, modid1: OXS.Ident; ccARCH: INTEGER);
— Write delivers a byte from the integer to the symbol file.
PROCEDURE Write(VAR R: Files.Rider; x: INTEGER);
— OutType writes a type to the symbol file
PROCEDURE OutType(VAR R: Files.Rider; t: Type);
- ::
PROCEDURE OutPar(VAR R: Files.Rider; par: Object; n: INTEGER);
- ::
PROCEDURE FindHiddenPointers(VAR R: Files.Rider; typ: Type; offset: LONGINT);
— Export writes out the symbol file for a module.
PROCEDURE Export*(VAR modid: OXS.Ident; VAR newSF: BOOLEAN; VAR key: LONGINT; ccARCH: INTEGER);
— Clear prepares the top scope of the program.
PROCEDURE Clear*;
— type allocates a pre-defined type object
PROCEDURE type(ref, form: INTEGER; size: LONGINT): Type;
— Enter introduces a pre-defined type, function, or procedure.
PROCEDURE Enter*(name: ARRAY OF CHAR; cl: INTEGER; type: Type; n: LONGINT);
— PrepSYSTEM prepares the SYSTEM scope for entry of types, functions, or procedures.
PROCEDURE PrepSYSTEM*;
— Init registers base Oberon types and populates the the object table with predeclared types,functions and procedures.
PROCEDURE Init*(wordsize: INTEGER);
Development Guide¶
(NW 25.6.2014 / AP 4.3.2020 / 8.3.2019 in Oberon-07 / CP 11.2020)
OXB is called from ORP and OXG and tracks the state of identifiers and objects as code compilation progresses.


 Implementing, debugging and maintaining such collectors can therefore be extremely challenging. The choice of implementation language is a crucial consideration when building a collector. Typically, the drive for performance and the need for efficient support of low-level memory operations leads to the use of low-level languages like C or C++, which offer little by way of safety and software engineering benefits. This risks undermining the robustness and flexibility of the collector design. Rust’s ownership model, lifetime specification, and reference borrowing deliver safety guarantees through a powerful static checker with little runtime overhead. These features make Rust a compelling candidate for a collector implementation language, but they come with restrictions that threaten expressiveness and efficiency. We describe our experience implementing an Immix garbage collector in Rust and C. We discuss the benefits of Rust, the obstacles encountered, and how we overcame them. We show that our Immix implementation has almost identical performance on micro benchmarks, compared to its implementation in C, and outperforms the popular BDW collector on the gcbench micro benchmark. We find that Rust’s safety features do not create significant barriers to implementing a high performance collector. Though memory managers are usually considered low-level, our high performance implementation relies on very little unsafe code, with the vast majority of the implementation benefiting from Rust’s safety. We see our experience as a compelling proof-of-concept of Rust as an implementation language for high performance garbage collection.
@inproceedings{Lin+2016ISMM, author = {Lin, Yi and Blackburn, Stephen M. and Hosking, Antony L. and Norrish, Michael}, title = {Rust as a language for high performance GC implementation}, booktitle = {ACM SIGPLAN International Symposium on Memory Management}, series = {ISMM}, year = {2016}, pages = {89-98}, month = {June}, address = {Santa Barbara, California}, doi = {10.1145/2926697.2926707} }


---
layout: default
title: Continuous Delivery on OpenShift
---
layout: true
name: top-bar
.left[![HealthPartners](/images/hplogo.gif)]
---
class: center
# Continuous Delivery on OpenShift
## Building a functional build/deploy system at HealthPartners
---
# Philosophies
1. High availability for production
2. Secure credentials for all environments
3. Good default behavior
4. Continuous delivery – on demand from the business perspective
5. Everything comes from source control
6. Keep things ephemeral, record externally
---
# Cluster Design
* Build tools run on bld1 cluster
* Applications have three environments (dev, uat, prod)
.center[![Clusters](/images/cluster-design.png)]
---
# Tools
* Jenkins
* Bitbucket and Gitlab (long story)
* Nexus and Artifactory (long story)
* Jira & HipChat
* Hashicorp Vault
* Fortify
* Sonarqube
* ServiceNow
---
# OpenShift Concepts
* `BuildConfig` object integrates with Jenkins using `openshift-sync` plugin
* Jenkins uses `openshift-login` plugin to delegate access
* Jenkins pod running in each OpenShift namespace
* Each team owns one or more namespaces
---
# Jenkins Concepts
* Shared libraries create functions that can be called from Jenkinsfile
* Groovy scripts stored in `vars/` directory
* Must declare `public def call()` method
* Groovy classes stored in `src/` directory
* Resources stored in `resources/` directory
* Loaded with `libraryResource` function
* More info at https://jenkins.io/doc/book/pipeline/shared-libraries/
---
# Let's Dive In
```groovy
library identifier: 'hp-pipeline-library@master', retriever: modernSCM(
[$class: 'GitSCMSource',
remote<EMAIL_ADDRESS>credentialsId: "${env.NAMESPACE}-bitbucketsecret"]
)
hpPipeline([
appName: "my-service",
deployPom: "my-service/pom.xml",
team: "Cloud"
])
```
.center[![BlueOcean](/images/jenkinsBO.png)]
---
# Developer Viewpoint
* Create your git repository with Jenkinsfile and pipeline.yaml at the root
* `oc login https://openshift-bld1.com && oc project MYPROJECT`
* `oc create -f pipeline.yaml`
* Jenkins pod in the namespace runs the build
---
# The Pipeline
1. Prepare
2. Build
3. Test
4. Pre-deploy
5. Deploy
6. Verify
7. Repeat 4-6
---
# The Code
hpPipeline.groovy
```groovy
def call(pipelineConfig) {
new PipelineWrapper(this).wrapPipeline(pipelineConfig) { config ->
def target = [namespace: env.NAMESPACE,
environment: OpenshiftEnvironments.getBuildEnvironment()]
DefaultEvaluator.evaluateDefault(config,
'buildStage')?.call(config, target, this)
def envArray = DefaultEvaluator.evaluateDefault(config,
'deploymentEnvironments').call(config)
for (String environment : envArray) {
target << [environment: environment]
beginEnvironment(environment, config)
deployToEnvironment(environment, config)
postDeployStages(environment, config)
}
}
}
```
---
# Preparation
* Set some base variables
```groovy
def wrapPipeline(pipelineConfig, closure) {
pipelineConfig.audit = [:]
pipelineConfig.defaults = new DefaultEvaluator().initialize()
if (!pipelineConfig.openshift) {
pipelineConfig.openshift = [:]
}
if (!pipelineConfig.skipNotify) {
pipelineConfig.skipNotify = false
}
pipelineConfig.pipelineJobId = UUID.randomUUID().toString()
...
```
---
# Preparation
* Tell people what is happening
```groovy
context.notifyHipChatRoom([
team: pipelineConfig.team,
message: "Jenkins build started: ${detail}",
skipNotify: pipelineConfig.skipNotify
])
context.audit([
message: "Jenkins build started",
build: context.env.BUILD_DISPLAY_NAME,
job: context.env.JOB_NAME
], pipelineConfig)
```
---
# Preparation
* Enforce specific properties
```groovy
if (!pipelineConfig.appName) {
error "You must define an appName property"
}
if(!pipelineConfig.team) {
error "You must define a team property"
}
```
---
# Preparation
* Set global environment variables for the job
```groovy
env.DOCKER_HOST = 'docker.healthpartners.com'
env.FORTIFY_CLD_CTRL_HOST = 'https://fortify.healthpartners.com/cloud-ctrl'
env.FORTIFY_SSC_HOST = 'https://fortify.healthpartners.com/ssc'
env.FORTIFY_TOKEN = 'my-fav-token'
env.MAVEN_IMAGE_HASH = 'sha256:abc123'
env.FORTIFY_IMAGE_HASH = 'sha256:def456'
env.NODE_IMAGE_HASH = 'sha256:ghi789'
env.JIRA_HOST = 'jira.healthpartners.com'
env.SONARQUBE_URL = "http://sonarqube.${env.NAMESPACE}.svc:9000".toString()
env.AUDIT_URL = 'https://auditing-service.healthpartners.com/'
```
---
# Tangent: Defaults and Overrides
* Goal: Be able to override anything
* Sensible defaults in a place you can find them
* Created a groovy specific structure Evaluator/Configurer
* Single place where defaults are stored and evaluated
* Each default contributor is specific to a category
* e.g. `MavenDefaultContributors`
---
# Tangent: Defaults and Overrides
* Groovy truthiness makes life easy here
```groovy
def evaluateDefault(config, String key) {
def overrides = config?.overrides?.get(key)
//single argument function
def metaClassArgs = overrides?.metaClass?.respondsTo(overrides,
'call', [Object.class].toArray())
if (overrides && metaClassArgs && !metaClassArgs.isEmpty()) {
return overrides.call(config)
} else if (overrides){
//its not a closure, so it must be a value: return it
return overrides
} else {
//attempt the default closure, then the default value
return defaultClosures?.get(key)?.call(config) ?:
defaultValues[key]
}
}
```
---
# Tangent: Defaults and Overrides
```groovy
class MavenDefaultContributors implements DefaultContributor {
@Override
LinkedHashMap getClosures() {
return [
packaging: {it.packaging},
compilePom: {it.pomPath ?: it.appDir ? it.appDir + "/pom.xml" : null},
packageFlags: {it.packageFlags ?: ''},
deployFlags: {it.deployFlags ?: ''},
integrationTestFlags: {it.integrationTestFlags ?: ''},
webTestFlags: {it.webTest?.mavenFlags ?: '' }
]
}
@Override
LinkedHashMap getValues() {
return [
packaging: 'jar'
]
}
}
```
---
# Tangent: Defaults and Overrides
* This structure allows developers to override anything that is keyed by a contributor
```groovy
hpPipeline([
...
overrides: [
packageFlags: "-PmyFavoriteProfile -Dprop=value"
]
])
```
---
# Build Stage
* Goal: Get a validated docker image to deploy
* Steps:
* Package artifact
* Run unit/component tests
* Run s2i build from base image
* Publish image to external registry
---
# Testing
* Unit & Component tests run before pre-deployment begins
* Generally JUnit tests, building @SpringBootTest component tests to load parts of the application
* H2 Database testing
---
# Pre-Deployment
* Approve the environment
* Check that the cluster is up
* Change management (will go into detail later)
```groovy
def call(envKey, config) {
def envConfig = OpenshiftEnvironments.getEnv(envKey)
getEnvironmentApproval(envConfig, config)
checkEnvironmentAvailability(envConfig)
jiraValidator(config, envConfig)
changeStart(config, envConfig)
}
```
---
# Deployment
* Use the API to update the deploymentconfig and associated objects
* Right now, we are using Jenkins to generate YAML file manifest
```groovy
def objects = [
'BuildConfig' : new BuildConfig().create(config, target),
'ImageStream' : new ImageStream().create(config, target),
'DeploymentConfig' : new DeploymentConfig().create(config, target),
'Service' : new Service().create(config, target),
]
```
---
# Verification
* Post deployment separated into "Phases" and run in parallel
* SonarQube scan phase
* Fortify scan phase
* Separate scan from validating results
* Integration tests live with the source code
* Zephyr tests from JIRA
* Selenium tests through a Selenium grid
* Change management verification
---
# Verification
```groovy
if(!config.buildOnly) {
addPhase(postDeployMap, new IntegrationTestPhase(this),
environment, config, null)
}
if (config.zephyr) {
if (config.zephyr.environments.contains(environment)) {
addPhase(postDeployMap, new ZephyrTestPhase(this),
environment, config, null)
}
}
if (project.buildType == 'maven') {
if (environment.contains('dev')) {
addPhase(postDeployMap,
new StaticCodeScanPhase(this), environment, config,
[new SonarQubeReporting(this), new FortifyReporting(this)])
}
else if(environment.contains('uat'))
{
addPhase(postDeployMap,
new StaticCodeValidationPhase(this),
environment, config, null)
}
}
```
---
# Change Management
* ServiceNow TableAPI
* Much of the actions in the ServiceNow UI are available via API
* Standard change request process
* Change request templates that can be instantiated to changes
* Simplifies approval process for low priority changes
* Opt in:
```groovy
hpPipeline([
...
cmdb_item: "HealthPartners.com Services",
autoCreateChange: true,
...
])
```
---
# Change Management
* Created a Jenkins plugin to carry out standard actions
* https://github.com/jenkinsci/service-now-plugin
* Manage tables
* Attach files
* Update state
* Provides a simple entrypoint for making the necessary API calls
---
# Change Management
* Remember the philosophy: Keep things ephemeral, record externally
* ServiceNow is our main audit store
* Test results
* JIRA ticket number
* Git commit info
* Scan results
* Deployment time
* Deployment results
---
# Change Management: Results
* Can go from commit to production in 18 minutes
* Have completed over 10 deploys in a single day
* Multiple other companies using our plugin
* Validated our change management approach with our audit/compliance groups
---
# Visualizing the Data
* Created our own audit datastore and send data to Splunk
* Splunk: Short term event view
* Data store: Long term auditing view of things that happen in the pipeline
* Approvals
* Jobs
* Deployments
* Validations
---
# Visualizing the Data
.center[![Deployments](/images/deploymentLog.png)]
---
# Multi-Faceted Approach
* This is one of many of these libraries we have written:
* Liquibase pipelines
* ConfigMap and Secret management
* Namespace management
* Orchestrate Ansible Tower jobs for OpenShift infrastructure
* Even manage our weblogic servers through these pipelines(!)
---
# Building for the future
* Istio for canary deployments and advanced deployment strategy
* More complete testing strategies
* Read data from metrics stores to know about deployment success
* Tracking historical data
---
# OpenSource
* Working to open-source hp-pipeline-library
* Open sourced our testing library
* Our team manages two Jenkins plugins (service-now and prometheus)
* Open sourced a library that translates Prometheus alerts to ServiceNow (Snogo)
* Looking for more ways to contribute to the community
---
# References
1. https://github.com/jenkinsci/service-now-plugin
2. https://github.com/HealthPartners/jenkins-shared-library-test-helper
3. https://github.com/HealthPartners/snogo
4. https://jenkins.io/doc/book/pipeline/shared-libraries/


Congratulations, you successully deployed a Web+ application to your dedicated environment.
Please follow these steps to find out what you can do next according to the deployment method, then keep on reading the rest sections to learn more about Web+.
$ git checkout next-step
$ mvn clean package
$ wpctl deploy
The easiest way to run and manage your applications in Alibaba Cloud.
Rapid deploy predefined or fully customized application environments using web console or CLI tools.
Operate or maintain your application environments in one place without much more pain.
Watching your system or applicaton monitoring data without any configuration.
Stay tuned ...


+++ title = "Morning view from Patanuk" slug = "morning-view-from-patanuk" date = 2007-09-02T10:00:00+10:00 tags = ["lakes", "stunning"] locations = ["argentina/bariloche"] draft = false summary = """
I woke up this morning, in my dorm room at Patanuk, to be greeted with an amazing view of the lake, straight out of my window. Daym, this has gotta be the best view out of any hostel dorm room in the world! Patanuk is not a bad place to stay, not a bad place at all. Downstairs, that much-anticipated free breakfast of croissants and scones (with fresh, home-made strawberry jam on the side) was the icing on the cake; and the view of the lake was just as divine from the dining room.
""" +++I woke up this morning, in my dorm room at Patanuk, to be greeted with an amazing view of the lake, straight out of my window. Daym, this has gotta be the best view out of any hostel dorm room in the world! Patanuk is not a bad place to stay, not a bad place at all. Downstairs, that much-anticipated free breakfast of croissants and scones (with fresh, home-made strawberry jam on the side) was the icing on the cake; and the view of the lake was just as divine from the dining room.
{{< galleryphoto "2007-09-02-10-00-00--that-s-what-i-call-a-room-with-a-view.jpg" >}}


This library integrates the Google Earth API, and will render most map overlays appropriately.
To initialize the Earth API, just instantiate a new GoogleEarth object, passing your map to it. Here is the simplest case of a map with no overlays:
var myOptions = { zoom: 4, center: new google.maps.LatLng(48.25, 11.00), mapTypeId: google.maps.MapTypeId.ROADMAP }; var map = new google.maps.Map(document.getElementById('map'), myOptions); var ge = new GoogleEarth(map);
The current version of this library also supports a number of different overlays and layers. If you add any of the following to your map, they will also be displayed in Earth: Marker, InfoWindow, Polyline, Polygon, Rectangle, Circle, GroundOverlay and KmlLayer.
For an example that makes use of all these, check out earth.html.
| Constructor | Description |
|---|---|
GoogleEarth(map:google.maps.Map) |
A wrapped Google Earth API instance, linked to the map. |
| Constant | Description |
|---|---|
MAP_TYPE_ID |
This map type displays the 3D Earth Plugin |
| Methods | Return Value | Description |
|---|---|---|
getInstance() |
google.earth.GEPlugin |
The Earth API instance |


Email address is required.
Email address is invalid.
First name is required.
Last name is required.
{{x}}
Password is required.
{{passwordError}}
Registered No is required.
Year Of Study is required.
Branch is required.
Role is required.


Username *Required
e-mail address *Required
Phone Number *Required
Address *Required
Credit Card Number *Required
Photo of passport *Required
Work Address *Required
All family member contact numbers *Required
Car licence plate number *Required
Address *Required
PayPal username and password *Required
Photo of drivers license *Required


{% extends 'base.html' %} {% block body %}
Considering huge amount text needed to be searched while finding the answer, we would like to first find possible paragraphs to narrow down the search area, which is so called the candidate retrieval. The document uploaded is first segmented in different paragraphs. Each paragraph would be encoded as bag of words. With the feature vectors representing paragraphs, we do spectral clustering with a rbf kernel on them. The resulting clusters are different topics we would like to retrieve.
For the retrieval process where we are given a question, we measure the cosine similarity between the question and every paragraph. Take the paragraph closest to the question and retrieve the whole cluster that paragraph belongs to. That cluster of paragraphs would be our candidates for answering questions.
The model we are using is called Reinforced Mnemonic Reader (Hu et al. 2018). The architecture of the model is shown below
The key idea of the model is basically attending the context, which is the candidate paragraphs after our retrieval, with the question user asked. This attentive information is then combined with the context with a fusion function to produce a question-attend context feature. This is then self attended to capture long term dependencies among context words. After this whole process, a biLSTM is used and we can then answer the question based on the question attended context.
The duplicate question caching system is intended to speed up the answering process for questions that
have already been answered. The site caches recent questions so that when a question is asked again, if it
is a duplicate of a question that has already been asked, we fetch the answer from the cache and do not
need to query the neural network again.
Traditionally duplicate question detection is done via a Siamese neural network, which uses two identical
neural networks with shared weights to compute the similarity and decide whether it has the potential to
be a duplicate. Though this approach has decent accuracy, it requires a neural network to encapsulate an
entire natural language question as a single finite-dimensional embedding, which is a daunting task.
In an effort to look for a better way to detect duplicate questions, I was inspired by the attention
mechanism, and how it achieves much better performance than summarization with a single embedding by looking at
the entire sentence at once. Thus I developed a duplicate questions framework based on a Sequential Least Squares
Programming (SLSQP) solver.
I couldn't use equality for SLSQP, had to bound the solution. Had to adapt entropy a tiny bit to return 0 for 0 inputs. Weights were
constrained to be greater than 0 and less than 1. There are some interesting side effects of this approach as well, such that when there
is padding or an unknown word, the weights solved for are all 0, which intuitively means that these provide no information.
This model achieves 70% validation accuracy, with around 83% training accuracy, and does not outperform the Siamese network, but
this is to be expected. There are two main flaws with this approach, though there are clear paths to resolve them.
Firstly, there is no recognition of different words (two questions sharing "the" is equivalent them sharing "eucalyptus"),
and this could be mitigated by relying on tf-idf weighting or a similar mechanism to make rarer words in the corpus more "valuable".
Secondly, there the constrained optimization method is rather inexpressive as it relies on very simple relationships such
as weighted sums, and I feel like the use of a neural network in a similar context would have a lower bias.


QueueRunner
Holds a list of enqueue operations for a queue, each to be run in a thread.
tf.compat.v1.train.queue_runner.QueueRunner
Queues are a convenient TensorFlow mechanism to compute tensors asynchronously using multiple threads. For example in the canonical 'Input Reader' setup one set of threads generates filenames in a queue; a second set of threads read records from the files, processes them, and enqueues tensors on a second queue; a third set of threads dequeues these input records to construct batches and runs them through training operations.
There are several delicate issues when running multiple threads that way: closing the queues in sequence as the input is exhausted, correctly catching and reporting exceptions, etc.
The QueueRunner
, combined with the Coordinator
, helps handle these issues.
QueueRunners are not compatible with eager execution. Instead, please
use tf.data
to get data into your model.
__init__
__init__( queue=None, enqueue_ops=None, close_op=None, cancel_op=None, queue_closed_exception_types=None, queue_runner_def=None, import_scope=None )
Create a QueueRunner. (deprecated)
Warning: THIS FUNCTION IS DEPRECATED. It will be removed in a future version.
Instructions for updating:
To construct input pipelines, use the tf.data
module.
On construction the QueueRunner
adds an op to close the queue. That op
will be run if the enqueue ops raise exceptions.
When you later call the create_threads()
method, the QueueRunner
will
create one thread for each op in enqueue_ops
. Each thread will run its
enqueue op in parallel with the other threads. The enqueue ops do not have
to all be the same op, but it is expected that they all enqueue tensors in
queue
.
queue
: A Queue
.enqueue_ops
: List of enqueue ops to run in threads later.close_op
: Op to close the queue. Pending enqueue ops are preserved.cancel_op
: Op to close the queue and cancel pending enqueue ops.queue_closed_exception_types
: Optional tuple of Exception types that
indicate that the queue has been closed when raised during an enqueue
operation. Defaults to (tf.errors.OutOfRangeError,)
. Another common
case includes (tf.errors.OutOfRangeError, tf.errors.CancelledError)
,
when some of the enqueue ops may dequeue from other Queues.queue_runner_def
: Optional QueueRunnerDef
protocol buffer. If specified,
recreates the QueueRunner from its contents. queue_runner_def
and the
other arguments are mutually exclusive.import_scope
: Optional string
. Name scope to add. Only used when
initializing from protocol buffer.ValueError
: If both queue_runner_def
and queue
are both specified.ValueError
: If queue
or enqueue_ops
are not provided when not
restoring from queue_runner_def
.RuntimeError
: If eager execution is enabled.cancel_op
close_op
enqueue_ops
exceptions_raised
Exceptions raised but not handled by the QueueRunner
threads.
Exceptions raised in queue runner threads are handled in one of two ways
depending on whether or not a Coordinator
was passed to
create_threads()
:
Coordinator
, exceptions are reported to the coordinator and
forgotten by the QueueRunner
.Coordinator
, exceptions are captured by the QueueRunner
and
made available in this exceptions_raised
property.A list of Python Exception
objects. The list is empty if no exception
was captured. (No exceptions are captured when using a Coordinator.)
name
The string name of the underlying Queue.
queue
queue_closed_exception_types
create_threads
create_threads( sess, coord=None, daemon=False, start=False )
Create threads to run the enqueue ops for the given session.
This method requires a session in which the graph was launched. It creates
a list of threads, optionally starting them. There is one thread for each
op passed in enqueue_ops
.
The coord
argument is an optional coordinator that the threads will use
to terminate together and report exceptions. If a coordinator is given,
this method starts an additional thread to close the queue when the
coordinator requests a stop.
If previously created threads for the given session are still running, no new threads will be created.
sess
: A Session
.coord
: Optional Coordinator
object for reporting errors and checking
stop conditions.daemon
: Boolean. If True
make the threads daemon threads.start
: Boolean. If True
starts the threads. If False
the
caller must call the start()
method of the returned threads.A list of threads.
from_proto
@staticmethod from_proto( queue_runner_def, import_scope=None )
Returns a QueueRunner
object created from queue_runner_def
.
to_proto
to_proto(export_scope=None)
Converts this QueueRunner
to a QueueRunnerDef
protocol buffer.
export_scope
: Optional string
. Name scope to remove.A QueueRunnerDef
protocol buffer, or None
if the Variable
is not in
the specified name scope.


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--- title: TheCurriedBlog ---
Being a functional programming enthusiast, the name of the Blog seems apt. So is it just the name? Not exactly. I will aim that my blog posts build on each other to present something that will help someone.
…or you can find more in the archives.


Part 0: Setup
Initial setup for our Network/IRC Bot Tutorial.
Setup
IMPORTANT: Please be sure to work through the machine setup before proceeding.
Within your terminal:
cd
to get to your “Home” directory- If you haven’t already made a
Projects
folder for your new coder projects (or perhaps named it something else), then:$ mkdir Projects
to create a new 'Projects' folder. You can name it whatever you want, just remember what you named it, and where it is. - Move into your
Projects
directory (or whatever you named it to):cd Projects
. - If you haven’t already cloned the repo, then
$ git clone https://github.com/econchick/new-coder.git
. This clones the New Coder project into the directory you're currently in, which is Projects (unless you named it something else). $ cd new-coder/network
Change into the Network tutorial.- If you have virtualenvwrapper and followed the steps above from Initial Requirements installed (which you should if you are on Mac or Linux, follow machine setup if not):
$ mkvirtualenv NetworkProj
Make a virtual environment specific to your Network project. You should see(NetworkProj)
before your prompt, now. - If you have Windows, within your Python project directory, type:
virtualenv.py NetworkProj
. A virtual environment called “NetworkProj” will be started. Now you will need to activate it, type:NetworkProj\Scripts\activate.bat
and you’ll see something like(NetworkProj) C:\PythonProjects>
(NetworkProj) $ pip install -r requirements.txt
Now installing package requirements for this project. Your virtual environment will store the required packages in a self-contained area to not mess up with other Python projects.
Now you’re ready to move onto defining our bot settings →


Favorite Places
Written with the guidance of Epicodus
These are our favorite places
Victoria, BC
Tokyo, Japan
London, UK
New York, USA
Cairo, Egypt
Rome, Italy
Mexico City, Mexico
Baguio City, Philippines
Beijing, China
Rio de Janeiro, Brazil


{% extends "global/Base.html" %} {% load staticfiles otree_tags %} {% block title %} Willingness List {% endblock %} {% block scripts%} {% endblock %} {% block content %}
Your counterpart, A, has transferred {{a_takes_edited}}% of your income (${{taken_amount}}) to their own account. Your available earnings are now ${{available_earnings}}
What is the maximum amount you would be willing to pay to write and send a message that your counterpart A will read?
(Express the amount in dollars and cents)
{% formfield group.b_willing with label="How much will you pay?" %}The actual price of sending a message will be shown on the next screen.
{% next_button %} {% endblock %}


If the answer is no, they are not getting CDC’s recommended amount for youth. That means moderate-to-vigorous activity, with at least three of those days also involving exercise that strengthens muscles and bones.
Research shows that parents who are physically active are more likely to have physically active children. Be a role model, while also encouraging fun activities that you can enjoy together – from bike riding to a backyard catch.
Provide a child with the tools to play, on their own terms (not those of adults), and often they will. Unstructured play builds physical literacy and love of game, with intrinsic rewards that encourage further engagement.
The American Academy of Pediatrics recommends parents place consistent limits on time spent with media. Start by removing TVs from bedrooms. Research shows more than 1.5 hours of daily TV is a risk factor for obesity.
Most kids get funneled into the same, small handful of team sports. But there are 120 sports offered across the U.S., and some providers and sites might just be a few miles away. There’s a sport for every kid. Internet tools can help you explore.
Rock-climbing. Skiing. Snowshoeing. Martial arts. Archery. Individual sports can feel safe, especially for kids with special needs. Then there are more recreational team games, like Ultimate Frisbee.
Kids lacking physical confidence especially benefit from programs that foster a “mastery climate” in which development, not outcomes, is the goal. Ask programs for their mission statement — and how they define success.
Want more inclusive, development-focused policies in youth sports that make room for kids like yours? Do something about it and run for a town recreation board or youth sport program board. Get in there and change things.
These settings can engage all kids. But they’re under-resourced. The median P.E. budget for schools is $764 per year. Encourage your school board to make P.E. and recess available on a daily basis, led by trained instructors.
Organized leagues today can be costly, and a full-season commitment can cause a kid who doesn’t like the sport to turn off to sports in general. Find programs and camps that offer sport sampling, ideally at low or no cost.
0
your score
- 9-10 = Ideal scenario for kids
- 6-8 = Solid foundation
- 3-5 = Much more can be done
- 1-2 = Much more should be done
resource center
helpful links
The American Academy of Pediatrics provides information on the following topics:
- Encouraging your child to be physically active
- Find out what type of activities are advisable to introduce at each stage of development
- The importance of play in promoting healthy child development and maintaining strong parent-child bonds
- Is your child ready for sports?
- Choosing a sports program
- Organized sports for children and preadolescents
- The best ways to keep your child safe around swimming pools
- Understand ways to help children form and practice healthy media use habits
- Youth physical activity guidelines toolkit created by the Centers for Disease Control and Prevention and partner organizations.
- Influence of parents’ physical activity levels on activity levels of young children, Journal of Pediatrics
- Evaluating approaches to physical literacy through the lens of positive youth development, by Veronica Allen, Jennifer Turnidge & Jean Cote
- Centers for Disease Control and Prevention, SHAPE America, and other national organizations recommendations on daily recess physical activity
- What does the science say about athletic development in children?
- Physical literacy in the United States: A model, strategic plan, and call to action, Aspen Institute Sports & Society program, 2015.
- Check out a free, community-generated guide to parks and playgrounds, searchable by zip code, created by KaBOOM!
- The United States Olympic Committee, in partnership with national governing bodies of sport, created the American development model in 2014 to help Americans realize their full athletic potential and utilize sport as a path toward an active and healthy lifestyle.


Open a browser window and go to the following Web page:
Find the relevant ZIP file for the current version (e.g., daVinci_04.zip)
Download the ZIP file from the browser by using the
Save Link As... (or similar) command on the context menu
(right mouse button on Windows),
placing the ZIP file somewhere on your local disk.
After downloading, unzip the contents into a directory somewhere on your system.
Expected results
The directory should contain the following files:
configuration/
.eclipseproduct/
davinci.local.mac.command
davinci.local.win.bat
davinci.server.mac.command
davinci.server.win.bat
eclipse.exe
plugins/
Launch the daVinci server (need to run tests on both Windows and Mac)
Steps
With the Explorer (Windows) or Finder (Mac), navigate to the directory into which you unzip-d the daVinci files
Launch the daVinci server process:
On Windows, double-click on the file davinci.local.win.bat (Depending on your settings, the Windows explorer might not show the ".bat" extension)
On Mac, double-click on the file davinci.local.mac.command (Depending on your settings, the Mac finder might not show the ".command" extension)
Expected results
You can tell that the server has launched if you see the following message in the shell window:
!!!!!!!!!!!!!!
NOTE: CLOSING THIS WINDOW WILL
STOP THE DAVINCI SERVER PROCESS
!!!!!!!!!!!!!
Using directory: .....
osgi>
The daVinci server will continue to run until you close the shell window that comes up after you double-click on the server launch file.
Therefore, if you close the shell window, the daVinci server process will stop running,
at which point you can't run http://localhost:8080/davinci anymore.


The bar graph shows the Top 10 busiest Airport based on along with their flight volumes for 5 years (2004-2008).This analysis can be used to compare the top 10 busiest airports in terms of Flight Count
Maximum: William BHeartsfield, Atlanta
Count:4.17M flights
Minimum:Detroit Metropoliton - wayne county
count:1.50M flights
The map shows average arrival delay for each state based on the Inbound Traffic.The darker shade shows the state with high arrival delays.
Maximum: New Jersey (darkest shade) with an average arrival delay of approximately 20 minutes.
The bubble shows the states with the state initals in it. The size of the bubbles depends on the flight traffic (inbound) in that state. Bigger bubbles show more flight traffic
Maximum: CA (California) with grey bubble with maximum size
Minimum: VI(Virgin Island) next to MA(blue) with least size
Year:2008
This chart shows the comparison of airline departure delay for each month in 2008 and 2007. December is the month with maximum average delay followed by June,July and August.
For 2007, June has been the worst with maximm average departure delay.
Probably, worst weather in december could have impacted the maximum flight departures
A radar chart is a graphical method of displaying Average departure delay in the form of a two-dimensional chart with average delay being quantitative variables represented on axes starting from the same point
Analysis: August,June,July and Decembe shows increase in flight departure delay.
Summer vacation and winter weather could be reasons impacting the flight delays
From the graph, we can deduce that 2007 had highest number of flights delayed because of weather as compared to other years. We can also see that 2007 also had maximum Late Aircrafts. Weather could be one of the contributing factors towards late aircraft delay in year 2007
The pyramid shows that delay distribution by delay type.The height of each layer shows that average delay by perticular type. The base represents the number of times the aircraft has been delayed because of that perticular factor (delay type)
Analysis: Late Aircraft has maximum average delay in last five years hence shown with maximum height. It contributes about 35.97% of the total delay
The carrier delay has the maximum base which means that maximum number of flights were impacted with this type of delay
The locations on the map shows the busiest route by flight volume. This analysis can be used to understand the air traffic and congestion on this route
Locations:
Los Angeles International Airport
San Diego International-Lindberg
Flight Count:
68359
The network navigator shows the connections of airports. Nodes represent the airports (by iata code) and edges represents the routes(connections).
This analysis can be used to identify the connection between the airports
Thickness of the route is depends on number of flights on that route
The above map shows different possibe options on a single day of the month for flying from one state to another from different airport. One can choose the convinient flight by chosing to travel to nearby airport (within Illinois ) to fly to specific destination (California).
There could be multiple reasons for chosing different airport to fly:
1.Cost
2.Time
3.Convinience
Above graph shows all possible flights shceduled from nearby airports within illinois to callifornia for one specific day of the month
Following analysis uses Pearson Correlation to identify the relation between the aircraft's manufacturing year and the flight delays.
Pearson Correlation coefficient is the measure of linear correlation between two variables X and Y where X is the Year of manufacture and Y is the Average delay for all the aircrafts manufactured in that Year.
First Map Reduce job reads each line of the record and uses the distributed cache to get the year of manufature for the flights by Tail Number and calculates the average of delays for all the flights manufatcured in that year. Second job takes the input from the first job and Calculates the Pearson Correlation coefficient.
The relationship between two factors is identified by following :
0.1 < |r| < 0.3 => small correlation
0.3 < |r| < 0.5 => Moderate correlation
|r| > 0.5 => strong correlation
The result obtained for finding the relation between the Year of manufacture for a perticular flight and the Average delay for all the Aircraft manufactured in that year is 0.2896.
With this result, we can deduce that the Older or Newer aircrafts do not have much relation with Flight delays.
The line graph shows the comparison of 5 different airlines in each year. With the help of this graph, we can deduce that Southwest is the most preferred airline in all 5 years (2004-2008). In 2008, the number of scheduled flights has gone upto 1.20 M which is quite high when compared to other four airlines.
It clearly states that southwest has been leading the airlines industry since 2004. It also shows that south west has shown continuos increase throught out
With the help of this prediction, we can determine the approximate delay for a perticular flight.The prediction is performed by using the data set which has been produced by a map reduce job.Following factors have been taken into consideration for prediction:
1. Flight Number
2. Day of the month
3. Month
4. Delay for that flight on that perticular day
Training Data: 75% of whole
Testing Data: 25% of whole
Regression Technique: Linear Regression
Linear Regression is an approach for modeling the relationship between a scalar dependent variable Y which is Average Delay and one or more explanatory variables (Flight Number, Day of the Month, Month) denoted X.


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{% extends "base.html" %} {%- block title %}Dashboard{% endblock %} {%- import 'forms.html' as forms -%} {% block content %}


#include <ximath.h>
Public Member Functions | |
| CxPoint2 () | |
| CxPoint2 (float const x_, float const y_) | |
| CxPoint2 (CxPoint2 const &p) | |
| float | Distance (CxPoint2 const p2) |
| float | Distance (float const x_, float const y_) |
Public Attributes | |
| float | x |
| float | y |
| CxPoint2::CxPoint2 | ( | ) |
| CxPoint2::CxPoint2 | ( | float const | x_, | |
| float const | y_ | |||
| ) |
| CxPoint2::CxPoint2 | ( | CxPoint2 const & | p | ) |
| float CxPoint2::Distance | ( | CxPoint2 const | p2 | ) |
| float CxPoint2::Distance | ( | float const | x_, | |
| float const | y_ | |||
| ) |
| float CxPoint2::x |
| float CxPoint2::y |


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Table of Contents
Short Sword
Sword and Buckler
Grappling
Dagger
Short Sword
Sword and Buckler
Sword and Buckler 1
Sword and Buckler 2
Sword and Buckler 3
Sword and Buckler 4
Sword and Buckler 5
Sword and Buckler 6
Grappling
The First Wrestling
The Second Wrestling
The Third Wrestling
The Fourth Wrestling
The Fifth Wrestling
The Sixth Wrestling
The Seventh Wrestling
The Eighth Wrestling
The Ninth Wrestling
The Tenth Wrestling
The Eleventh Wrestling
The Twelfth Wrestling
The Thirteenth Wrestling
The Fourteenth Wrestling
The Fifteenth Wrestling
The Sixteenth Wrestling
The Seventeenth Wrestling
Dagger
Dagger 1
Dagger 2
Dagger 3
Dagger 4
Dagger 5
Dagger 6
Dagger 7